Update report_thesis/src/sections/related_work.tex

Co-authored-by: Pattrigue <[email protected]>

report_thesis/src/sections/related_work.tex

@@ -59,8 +59,8 @@ \subsection{Dimensionality Reduction Techniques}
 Additionally, \gls{pca} was used to discriminate individual rocks based on their overall elemental composition, effectively addressing matrix effects that can significantly impact the accuracy of analytical results.
 These studies, among others highlighted by \cite{pca_review_paper}, underscore the effectiveness of \gls{pca} as a preprocessing technique in \gls{libs} analysis.
 
-\citet{sirven_pca_ann_plsr} investigated the influence of matrix effects on the performance of quantitative analysis of chromium (\ce{Cr}) in soil samples using \gls{libs}. 
-\gls{pca} was used to classify spectra from two different soils and to detect outliers. 
-\gls{pca} was successful in separating spectra from agricultural soil and kaolinite in the plane of the first two components. 
-Additionally, \gls{pca} was employed to identify and remove outliers from the data set, enhancing the accuracy of subsequent analyses using \gls{ann}s and \gls{plsr}.
+\citet{sirven_pca_ann_plsr} investigated the influence of matrix effects on the performance of quantitative analysis of chromium (\ce{Cr}) in soil samples using \gls{libs}.
+\gls{pca} was used to classify spectra from two different soils and to detect outliers.
+It successfully separated spectra from agricultural soil and kaolinite in the plane of the first two components.
+Furthermore, \gls{pca} was used to identify and remove outliers from the dataset, enhancing the accuracy of subsequent analyses using \gls{ann}s and \gls{plsr}.
 This study demonstrated the utility of \gls{pca} in managing matrix effects and improving the accuracy of quantitative \gls{libs} analysis.